227-0973-00L Translational Neuromodeling
|Spring Semester 2021
|yearly recurring course
|Language of instruction
|Performance assessment information (valid until the course unit is held again)
|Performance assessment as a semester course
|graded semester performance
|Language of examination
|Repetition only possible after re-enrolling for the course unit.
|Good knowledge of principles of statistics,
good programming skills (MATLAB, Julia, or Python).
|Additional information on mode of examination
|Students are required to use one of the examples discussed in the course as a basis for developing their own generative model and use it for simulations and/or inference in application to a clinical question (a real or fictitious one).
This model is to be submitted as open source code (in MATLAB, Julia or Python), and the motivation and results are presented in a 15 min oral presentation followed by 15 min critical discussion. Group work (4-5 students) is required. The submitted code must be executable without any dependencies on specific operating systems or local setups.
Grading will depend on (i) originality of the question that is addressed, (ii) clarity, technical correctness and practicability of the code, (iii) the quality and clarity of the oral presentation, (iv) the quality and clarity of the written project report.
The code is to be submitted by 03.06.2021; the oral presentations take place on 04.06.2021.
Admission to the final project is subject to students having successfully obtained at least 40% of the points for each exercise (1 miss allowed) during the semester.